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semantic_model_delete

Destructive

Remove a semantic model from a Microsoft Fabric workspace by providing its workspace and model IDs.

Instructions

Delete a semantic model

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceIdYesThe workspace ID
semanticModelIdYesThe semantic model ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.8.0

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description merely restates the destructive action already indicated by annotations (readOnlyHint=false, destructiveHint=true) without adding context. It does not mention that deletion is permanent, whether dependent reports or artifacts are affected, or whether any confirmation or permission is required. The description adds no behavioral information beyond the annotations and schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence with no filler, front-loading the action immediately. However, it is so terse that it forgoes useful context such as permanence or prerequisites; this is still a conciseness strength rather than a verbosity problem. It would merit a 5 only if the brevity came with brief, high-value caveats.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive tool with no output schema, the description does not state what a successful delete returns, that the action is irreversible, or what preconditions exist. The two required IDs are fully covered by the schema and the destructive trait is in annotations, so the invocation itself is clear, but operational completeness is lacking. The one-line description leaves important decision-making context to the agent's assumptions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: workspaceId and semanticModelId are each described as 'The workspace ID' and 'The semantic model ID', so an agent has the needed meaning. The description itself contributes no parameter detail, which is acceptable under the high-coverage baseline. No enum or nested structure adds complexity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is a concise active statement — 'Delete a semantic model' — giving the exact verb and resource. Among the semantic_model_* siblings, no other operation performs deletion, so this cannot be confused with create, update, refresh, or read operations. It is minimal but unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no sentence about when to choose this tool, when not to use it, or which alternatives apply, such as using semantic_model_update_details to modify a model instead of deleting it. An agent discovers deletion only from the tool name and destructiveHint, not from any usage guidance. This leaves the 'when' entirely implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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